In OLTP (Online Transaction Processing) systems, data is accessed and changed concurrently by multiple transactions and the database changes from one consistent state to another. An OLTP system always shows the latest state of our data, therefore facilitating the development of front-end applications which require near real-time data consistency guarantees.
However, an OLTP system is no island, being just a small part of a larger system that encapsulates all data transformation needs required by a given enterprise. When integrating an OLTP system with a Cache, a Data Warehouse or an In-Memory Data Grid, we need an ETL process to collect the list of events that changed the OLTP system data over a given period of time.
In this article, we are going to see various methods used for capturing events and propagating them to other data processing systems.